chore: 批量新增各类工具脚本与配置文件

1. 新增音频录制、下载、上传相关脚本 2. 新增数据库操作、API调用工具 3. 新增Excel数据处理脚本 4. 新增弱密码检测脚本
2026-06-14 17:47:15 +08:00
parent aac9f5934d
commit 2d8c1ea8f9
46 changed files with 11644 additions and 829 deletions
@@ -0,0 +1,114 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "fee9c5bf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "401\n",
+      "{'code': 'INVALID_API_KEY', 'message': 'Invalid API key'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "import requests\n",
+    "\n",
+    "base_url = \"https://console.pivotbak.cfd/v1\"\n",
+    "api_key = \"sk-e5246cf15eed1c8c1b94f172c95115de3ae5413eaa5b0366810fa7842de6ada1\"\n",
+    "\n",
+    "resp = requests.get(\n",
+    "    f\"{base_url}/models\",\n",
+    "    headers={\n",
+    "        \"Authorization\": f\"Bearer {api_key}\",\n",
+    "        \"Content-Type\": \"application/json\",\n",
+    "    },\n",
+    "    timeout=30,\n",
+    ")\n",
+    "\n",
+    "print(resp.status_code)\n",
+    "print(resp.json())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "c479e82c",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ModuleNotFoundError",
+     "evalue": "No module named 'curl_cffi'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
+      "Cell \u001b[1;32mIn[11], line 2\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mos\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mcurl_cffi\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m requests\n\u001b[0;32m      4\u001b[0m BASE_URL \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhttps://console.pivotbak.cfd/v1\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m      5\u001b[0m API_KEY \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msk-e5246cf15eed1c8c1b94f172c95115de3ae5413eaa5b0366810fa7842de6ada1\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
+      "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'curl_cffi'"
+     ]
+    }
+   ],
+   "source": [
+    "import os\n",
+    "from curl_cffi import requests\n",
+    "\n",
+    "BASE_URL = \"https://console.pivotbak.cfd/v1\"\n",
+    "API_KEY = \"sk-e5246cf15eed1c8c1b94f172c95115de3ae5413eaa5b0366810fa7842de6ada1\"\n",
+    "\n",
+    "headers = {\n",
+    "    \"Authorization\": f\"Bearer {API_KEY}\",\n",
+    "    \"x-api-key\": API_KEY,\n",
+    "    \"Accept\": \"*/*\",\n",
+    "    \"Content-Type\": \"application/json\",\n",
+    "    \"sec-ch-ua-platform\": '\"Windows\"',\n",
+    "    \"sec-ch-ua\": '\"Not-A.Brand\";v=\"24\", \"Chromium\";v=\"146\"',\n",
+    "    \"sec-ch-ua-mobile\": \"?0\",\n",
+    "    \"x-title\": \"Cherry Studio\",\n",
+    "    \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) CherryStudio/1.9.9 Chrome/146.0.7680.188 Electron/41.2.1 Safari/537.36\",\n",
+    "    \"HTTP-Referer\": \"https://cherry-ai.com\",\n",
+    "    \"Sec-Fetch-Site\": \"cross-site\",\n",
+    "    \"Sec-Fetch-Mode\": \"cors\",\n",
+    "    \"Sec-Fetch-Dest\": \"empty\",\n",
+    "    \"Accept-Encoding\": \"gzip, deflate, br, zstd\",\n",
+    "    \"Accept-Language\": \"zh-CN\",\n",
+    "    \"Priority\": \"u=1, i\",\n",
+    "}\n",
+    "\n",
+    "resp = requests.get(\n",
+    "    f\"{BASE_URL}/models\",\n",
+    "    headers=headers,\n",
+    "    impersonate=\"chrome136\",\n",
+    "    timeout=30,\n",
+    ")\n",
+    "\n",
+    "print(\"status:\", resp.status_code)\n",
+    "print(resp.text)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
@@ -0,0 +1,30 @@
+"input": "最近一次考试是什么？",
+"input": "最近一次数学考试的成绩情况",
+"input": "最近一次英语考试各班考得怎么样",
+"input": "最近一次语文考试全年级的平均分",
+"input": "最近一次考试是谁发布的？",
+"input": "帮我查一下期中相关的成绩批次",
+"input": "帮我看看最近一次数学考试的数据结构",
+"input": "帮我分析最近一次数学考试各班成绩情况",
+"input": "帮我看看最近一次数学考试整个年级的成绩概况",
+"input": "帮我分析最近一次数学考试的分数分布情况",
+"input": "帮我对比分析最近一次考试语文数学英语三个科目的成绩情况",
+"input": "帮我查一下白若耶是哪位学生",
+"input": "帮我看看白若耶最近整体成绩怎么样",
+"input": "把白若耶最近几次数学成绩列出来",
+"input": "白若耶最近10次数学考试的成绩趋势怎么样",
+"input": "只分析语文数学英语这三科，帮我看白若耶哪科强哪科弱",
+"input": "只看语文数学英语三科，白若耶偏科吗？",
+"input": "白若耶最近有没有退步预警？",
+"input": "帮我看看白若耶最近一次考试的成绩详情",
+"input": "先给我看看趋势分析有哪些可用参数和批次",
+"input": "帮我看一班最近几次数学考试的均分走势",
+"input": "帮我看最近几次数学考试整体均分变化",
+"input": "白若耶这次考试比上次是进步还是退步？",
+"input": "白若耶最近一次考试排第几名？",
+"input": "最近一次数学考试分段分析有哪些可用配置？",
+"input": "帮我看最近一次数学考试各分段人数分布",
+"input": "帮我看最近一次数学考试高分段有哪些学生",
+"input": "帮我比较最近两次数学考试各分数段人数变化",
+"input": "帮我对比分析语文数学英语三个科目在不同批次的成绩情况，按班级分组",
+"input": "帮我对比分析白若耶在语文数学英语三个科目的跨批次成绩"
@@ -0,0 +1,184 @@
+const BASE_URL = process.env.LANGGRAPH_URL || "http://192.168.0.100:2026";
+const ASSISTANT_ID = process.env.ASSISTANT_ID || "student_score";
+const QUESTION = process.env.QUESTION || "白若耶最近10次数学考试的成绩趋势怎么样";
+
+const CONTEXT = {
+  team_id: process.env.TEAM_ID || "19",
+  env: process.env.AGENT_ENV || "dev",
+};
+
+function parseJson(text) {
+  try {
+    return JSON.parse(text);
+  } catch {
+    return text;
+  }
+}
+
+async function createThread() {
+  const response = await fetch(`${BASE_URL}/threads`, {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify({}),
+  });
+
+  if (!response.ok) {
+    throw new Error(`create thread failed: ${response.status} ${await response.text()}`);
+  }
+
+  const thread = await response.json();
+  return thread.thread_id;
+}
+
+function pickFinalAnswer(data) {
+  if (!data || typeof data !== "object" || Array.isArray(data)) {
+    return "";
+  }
+
+  const renderAnswer = data.render_answer;
+  if (renderAnswer && typeof renderAnswer.answer === "string") {
+    return renderAnswer.answer;
+  }
+
+  if (typeof data.answer === "string") {
+    return data.answer;
+  }
+
+  return "";
+}
+
+function pickReasoning(data) {
+  if (!data || typeof data !== "object" || Array.isArray(data)) {
+    return "";
+  }
+
+  const renderAnswer = data.render_answer;
+  if (renderAnswer && typeof renderAnswer.reasoning === "string") {
+    return renderAnswer.reasoning;
+  }
+
+  if (typeof data.reasoning === "string") {
+    return data.reasoning;
+  }
+
+  return "";
+}
+
+function handleEvent(eventName, dataText, answerParts, finalAnswers) {
+  const data = parseJson(dataText);
+
+  if (eventName === "updates") {
+    const finalAnswer = pickFinalAnswer(data);
+    const reasoning = pickReasoning(data);
+    if (data && typeof data === "object" && !Array.isArray(data)) {
+      console.log(`\n[updates] ${Object.keys(data).join(", ")}`);
+    } else {
+      console.log("\n[updates]", data);
+    }
+    if (reasoning) {
+      console.log("\n[reasoning]");
+      console.log(reasoning);
+    }
+    if (finalAnswer) {
+      finalAnswers.push(finalAnswer);
+      console.log("\n[final.answer]");
+      console.log(finalAnswer);
+    }
+    return;
+  }
+
+  if (eventName === "messages") {
+    const messageChunk = Array.isArray(data) ? data[0] : undefined;
+    const content = messageChunk && typeof messageChunk.content === "string" ? messageChunk.content : "";
+    if (content) {
+      answerParts.push(content);
+      process.stdout.write(content);
+    }
+    return;
+  }
+
+  if (eventName) {
+    console.log(`\n[${eventName}]`, data);
+  }
+}
+
+async function readSse(response) {
+  if (!response.body) {
+    throw new Error("response body is empty");
+  }
+
+  const reader = response.body.getReader();
+  const decoder = new TextDecoder("utf-8");
+  const answerParts = [];
+  const finalAnswers = [];
+  let buffer = "";
+
+  while (true) {
+    const { value, done } = await reader.read();
+    if (done) break;
+
+    buffer += decoder.decode(value, { stream: true });
+    const events = buffer.split(/\r?\n\r?\n/);
+    buffer = events.pop() || "";
+
+    for (const rawEvent of events) {
+      let eventName = "";
+      const dataLines = [];
+
+      for (const line of rawEvent.split(/\r?\n/)) {
+        if (line.startsWith("event:")) {
+          eventName = line.slice("event:".length).trim();
+        } else if (line.startsWith("data:")) {
+          dataLines.push(line.slice("data:".length).trimStart());
+        }
+      }
+
+      handleEvent(eventName, dataLines.join("\n"), answerParts, finalAnswers);
+    }
+  }
+
+  if (buffer.trim()) {
+    handleEvent("", buffer.trim(), answerParts, finalAnswers);
+  }
+
+  return finalAnswers.at(-1) || answerParts.join("");
+}
+
+async function main() {
+  const threadId = await createThread();
+  const endpoint = `${BASE_URL}/threads/${threadId}/runs/stream`;
+  const started = Date.now();
+
+  console.log("=== LangGraph fetch stream test ===");
+  console.log(`base_url: ${BASE_URL}`);
+  console.log(`assistant_id: ${ASSISTANT_ID}`);
+  console.log(`thread_id: ${threadId}`);
+  console.log("");
+
+  const response = await fetch(endpoint, {
+    method: "POST",
+    headers: {
+      "Content-Type": "application/json",
+      Accept: "text/event-stream",
+    },
+    body: JSON.stringify({
+      assistant_id: ASSISTANT_ID,
+      input: { question: QUESTION },
+      context: CONTEXT,
+      stream_mode: ["updates", "messages-tuple"],
+    }),
+  });
+
+  if (!response.ok) {
+    throw new Error(`stream request failed: ${response.status} ${await response.text()}`);
+  }
+
+  const answer = await readSse(response);
+  const elapsed = ((Date.now() - started) / 1000).toFixed(2);
+  console.log(`\n\n=== done: ${elapsed}s, answer length: ${answer.length} ===`);
+}
+
+main().catch((error) => {
+  console.error(error);
+  process.exitCode = 1;
+});
@@ -0,0 +1,108 @@
+from __future__ import annotations
+
+import asyncio
+import os
+import sys
+from typing import Any
+
+from langgraph_sdk import get_client
+
+
+BASE_URL = os.getenv("LANGGRAPH_URL", "http://192.168.0.100:2026")
+ASSISTANT_ID = "student_score"
+QUESTION = "帮我看看白若耶同学的信息"
+CONTEXT = {
+    "team_id": "19",
+    "env": "dev",
+}
+
+
+if hasattr(sys.stdout, "reconfigure"):
+    sys.stdout.reconfigure(encoding="utf-8")
+
+
+def event_data(event: Any) -> Any:
+    if isinstance(event, dict):
+        return event.get("data")
+    return getattr(event, "data", None)
+
+
+def event_name(event: Any) -> str:
+    if isinstance(event, dict):
+        return str(event.get("event") or "")
+    return str(getattr(event, "event", ""))
+
+
+def pick_final_answer(data: Any) -> str:
+    if not isinstance(data, dict):
+        return ""
+    render_answer = data.get("render_answer")
+    if isinstance(render_answer, dict) and isinstance(render_answer.get("answer"), str):
+        return render_answer["answer"]
+    answer = data.get("answer")
+    return answer if isinstance(answer, str) else ""
+
+
+def pick_answer_source(data: Any) -> str:
+    if not isinstance(data, dict):
+        return ""
+    render_answer = data.get("render_answer")
+    if isinstance(render_answer, dict) and isinstance(render_answer.get("answer_source"), str):
+        return render_answer["answer_source"]
+    answer_source = data.get("answer_source")
+    return answer_source if isinstance(answer_source, str) else ""
+
+
+async def main() -> None:
+    client = get_client(url=BASE_URL)
+    thread = await client.threads.create()
+    answer_parts: list[str] = []
+    final_answers: list[str] = []
+
+    print("=== LangGraph updates + messages-tuple 流式调用 ===", flush=True)
+    print("[updates] 节点进度；[messages] 最终 Markdown token。", flush=True)
+    print("", flush=True)
+
+    async for event in client.runs.stream(
+        thread_id=thread["thread_id"],
+        assistant_id=ASSISTANT_ID,
+        input={"question": QUESTION},
+        context=CONTEXT,
+        stream_mode=["updates", "messages-tuple"],
+    ):
+        name = event_name(event)
+        data = event_data(event)
+
+        if name == "updates":
+            final_answer = pick_final_answer(data)
+            answer_source = pick_answer_source(data)
+            if isinstance(data, dict):
+                print(f"\n[updates] {', '.join(data.keys())}", flush=True)
+                render_answer = data.get("render_answer")
+                if isinstance(render_answer, dict):
+                    print(f"[render_answer.keys] {', '.join(render_answer.keys())}", flush=True)
+            else:
+                print(f"\n[updates] {data}", flush=True)
+            if answer_source:
+                print(f"[answer_source] {answer_source}", flush=True)
+            if final_answer:
+                final_answers.append(final_answer)
+                print("\n[final.answer]", flush=True)
+                print(final_answer, flush=True)
+            continue
+
+        if name == "messages":
+            if isinstance(data, list) and data:
+                message_chunk = data[0]
+                content = message_chunk.get("content") if isinstance(message_chunk, dict) else ""
+                if isinstance(content, str) and content:
+                    answer_parts.append(content)
+                    print(content, end="", flush=True)
+            continue
+
+    print("\n\n=== 最终 Markdown 长度 ===", flush=True)
+    print(len(final_answers[-1] if final_answers else "".join(answer_parts)), flush=True)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())